Optimizing PPDM Using SQL Server 2016 and SQL Azure

Transcription

1 Optimizing PPDM Using SQL Server 2016 and SQL Azure Conor Cunningham Partner Architect, SQL Core Engine

2 Who Am I? I ve been at Microsoft for 18 years building database engines I ve worked on Jet (Access), SQL Server CE/SQL Mobile, SQL Server I have worked a lot in the Query Processor/Optimizer spaces Today I am serving as the breadth architect for SQL Server s Engine I enjoy coming to conferences to hear how people use our software and how we can improve it further

3 Microsoft a leader for Magic Quadrant for Operational Database Management Systems 1 Furthest in vision and ability to execute Magic Quadrant for Business Intelligence and Analytics Platforms 2 A leader 8 years running Magic Quadrant for Data Warehouse Database Management Solutions 3 A leader for the fourth consecutive year [1] *Gartner Magic Quadrant for Operational Database Management Systems, by Donald Feinberg, Merv Adrian, Nick Heudecker, Adam Ronthal, October 2015 [2] *Gartner Magic Quadrant for Business Intelligence and Analytics Platforms, by Rita Sallam and Josh Parenteau, February 23, 2015 [3] *Gartner Magic Quadrant for Data Warehouse and Data Management Solutions for Analytics, by Mark Beyer and Roxane Edjlali, February 12, 2015 This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Microsoft. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

4 SQL Server 2016: everything built-in built-in built-in built-in built-in built-in $2, SQL Server SQL Server SQL Server #1 #2 #3 Oracle is #5 $480 $120 Microsoft Tableau Oracle SQL Server Oracle MySQL SAP HANA TPC-H non-clustered 10TB In-memory across all workloads Self-service BI per user Real time and at massive scale Consistent experience from on-premises to cloud The above graphics were published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Microsoft. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. National Institute of Standards and Technology Comprehensive Vulnerability Database update 10/2015 TPC-H non-clustered results as of 04/06/15, 5/04/15, 4/15/14 and 11/25/13, respectively.

5 SQL Server 2016 New Feature Summary Enhanced in-memory OLTP performance and surface area Operational analytics Enhanced AlwaysOn with no domain join (WS 2016) Query Store Temporal JSON Import/Export Always Encrypted Row-level security Dynamic data masking Enhanced separation of duties Enhanced SQL Server auditing Transparent data encryption Enhanced in-memory ColumnStore Performance Deployment rights for APS Distributed query processing to Hadoop (Polybase) PolyBase in scale-out configuration (head and compute nodes) End-to-end mobile BI on all major platforms Enhanced direct query In-memory analytics Advanced data mining Advanced tabular modeling (250+ functions) Web portal experience Modernized reports (all reports in one place) In database Advanced Analytics Connectivity to R Open R integration with massive parallel processing for performance and scale Works with in-memory technology Run in database or standalone Stretch Database Enhanced backup to Azure Enhanced HA and DR with Azure ease of use, no domain join (WS2016) SSIS integration with Azure Data Factory and Azure SQL Data Warehouse Pin reports to Power BI

6 Demo PPDM 3.9 on SQL Server 2016

7 PPDM 3.9 Additions Increased Foreign Key Reference Support (tested to 10,000) PPDM 3.9 has ~3000 or so Operational Analytics Non-Clustered Columnstore support over B-Tree indexes for increased reporting performance Query Store for better diagnostics over query performance investigations General Perf/Scale Improvements on Large Hardware vs. SQL 2014